{"title":"Knowledge and Practice changes following a student data focused data management education program.","authors":"Tina Griffin","doi":"10.31274/JLSC.12906","DOIUrl":null,"url":null,"abstract":"Introduction\nIt is known that graduate students work with research data more intimately than their faculty mentors. Because of this, much data management education is geared toward this population. However, student learning has predominantly been assessed through measures of satisfaction and attendance rather than through evaluating knowledge and skills acquired. This study attempts to advance assessment efforts by asking students to report their knowledge and practice changes before, immediately after, and six months following education. \nMethods\nGraduate students in STEM and Health sciences disciplines self-enrolled in an eight-week data management program that used their research projects as the focus for learning. Three surveys were administered (pre, post, and six months following) to determine changes in students’ knowledge and practices regarding data management skills. The survey consisted of approximately 115 Likert-style questions and covered major aspects of the data life cycle. \nResults & discussion\nOverall students increased their data management knowledge and improved their skills in all areas of the data life cycle. Students readily adopted practices for straightforward tasks like determining storage and improving file naming. Students improved but struggled with tasks that were more involved like sharing data and documenting code. For most of these practices, students consistently implemented them through the six month follow up period. \nConclusion\nImpact of data management education lasts significantly beyond immediate instruction. In depth assessment of student knowledge and practices indicates where this education is effective and where it needs further support. It is likely that this effect is due to the program length and focus on implementation. \n","PeriodicalId":91322,"journal":{"name":"Journal of librarianship and scholarly communication","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of librarianship and scholarly communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31274/JLSC.12906","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction
It is known that graduate students work with research data more intimately than their faculty mentors. Because of this, much data management education is geared toward this population. However, student learning has predominantly been assessed through measures of satisfaction and attendance rather than through evaluating knowledge and skills acquired. This study attempts to advance assessment efforts by asking students to report their knowledge and practice changes before, immediately after, and six months following education.
Methods
Graduate students in STEM and Health sciences disciplines self-enrolled in an eight-week data management program that used their research projects as the focus for learning. Three surveys were administered (pre, post, and six months following) to determine changes in students’ knowledge and practices regarding data management skills. The survey consisted of approximately 115 Likert-style questions and covered major aspects of the data life cycle.
Results & discussion
Overall students increased their data management knowledge and improved their skills in all areas of the data life cycle. Students readily adopted practices for straightforward tasks like determining storage and improving file naming. Students improved but struggled with tasks that were more involved like sharing data and documenting code. For most of these practices, students consistently implemented them through the six month follow up period.
Conclusion
Impact of data management education lasts significantly beyond immediate instruction. In depth assessment of student knowledge and practices indicates where this education is effective and where it needs further support. It is likely that this effect is due to the program length and focus on implementation.